Published Technical Disclosure Archive

Next-Generation Tennis Stroke Heaviness Assessment and Training

Publication ID: 24-11857862_0005_PTD
Published: October 28, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Tennis Stroke Heaviness Assessment and Training,” Published Technical Disclosure No. 24-11857862_0005_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857862_0005_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,862.

Summary of the Inventive Concept

A comprehensive system for simulating, predicting, and providing real-time feedback on tennis stroke heaviness, enabling personalized training programs and biomechanical analysis.

Background and Problem Solved

The original patent provided a method and system for assessing tennis stroke heaviness, but it was limited to quantifying heaviness using sensors and processors. The new inventive concept addresses the need for more advanced, forward-thinking solutions that integrate machine learning, virtual environments, and wearable devices to revolutionize tennis training and analysis.

Detailed Description of the Inventive Concept

The next-generation system comprises a neural network trained on a dataset of tennis strokes, a physics engine generating virtual tennis ball trajectories, and a wearable device providing real-time feedback on stroke heaviness. The system can also generate personalized training programs based on a player's stroke heaviness and evaluate stroke heaviness using biomechanical analysis. These components work together to provide a holistic, data-driven approach to tennis training and analysis.

Novelty and Inventive Step

The new inventive concept introduces the use of machine learning, virtual environments, and wearable devices to assess and train tennis stroke heaviness, which is a significant departure from the original patent's sensor-based approach. The integration of these advanced technologies enables a more comprehensive and accurate assessment of stroke heaviness, providing a substantial improvement over existing methods.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of augmented reality, computer vision, or other sensing technologies to assess stroke heaviness. Variations could also include the development of specialized training programs for specific tennis strokes or player types.

Potential Commercial Applications and Market

The next-generation tennis stroke heaviness assessment and training system has significant commercial potential in the tennis industry, with potential applications in professional training, amateur coaching, and sports equipment manufacturing. The system could also be adapted for use in other racquet sports or athletic training programs.

CPC Classifications

SectionClassGroup
A A63 A63B71/0622
A A63 A63B43/004
A A63 A63B69/38
A A63 A63B2071/0625
A A63 A63B2214/00
A A63 A63B2220/05
A A63 A63B2220/20
A A63 A63B2220/35
A A63 A63B2220/62
A A63 A63B2220/806
A A63 A63B2220/808
A A63 A63B2220/89

Field of Art

Sports Technology, Biomechanical Analysis, Motion Tracking Systems, and Athletic Performance Measurement with expertise in sensor technologies, machine learning, and motion capture techniques

Person of Ordinary Skill (PHOSITA) Profile

A technical professional with advanced degrees in engineering, computer science, or sports science, possessing skills in sensor design, data analysis, machine learning algorithms, and understanding of athletic biomechanics

Obviousness Rationale

A PHOSITA would recognize that extending the source patent's tennis stroke heaviness measurement system through machine learning, virtual simulation, and personalized training is a natural progression of existing sensor-based motion tracking technologies. The fundamental concept of quantifying tennis stroke characteristics remains consistent, with the PTD merely introducing more sophisticated computational and predictive techniques. These variations represent incremental technological improvements using standard machine learning and sensor integration approaches that would be readily conceived by a skilled practitioner.

Obvious Combinations & Variations

Source Patent Element
Sensor device detecting tennis ball movement parameters and generating heaviness value
PTD Variation
Neural network trained on tennis stroke dataset to predict heaviness value
Obviousness Reasoning
Predictable application of machine learning to existing sensor-based measurement technique, representing a known method of enhancing data interpretation through statistical modeling
Source Patent Element
Translational and rotational kinetic energy calculations for stroke assessment
PTD Variation
Physics engine generating virtual tennis ball trajectories based on neural network output
Obviousness Reasoning
Logical extension of existing kinematic modeling using computational simulation techniques, representing a standard approach to enhancing predictive capabilities
Source Patent Element
Sensor system for measuring ball movement characteristics
PTD Variation
Wearable device providing real-time feedback on stroke heaviness
Obviousness Reasoning
Obvious design variation using miniaturized sensor technology and display integration, representing a standard method of making measurement systems more user-accessible
Source Patent Element
System for assessing tennis stroke parameters
PTD Variation
Biomechanical analysis using 3D motion capture to determine stroke heaviness
Obviousness Reasoning
Predictable technological progression using advanced motion tracking techniques, representing a known approach to enhancing measurement precision
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857862 and the disclosed technical variations, a person having ordinary skill in the art would find the claimed innovations obvious and lacking inventive step. The published technical disclosure demonstrates that the proposed system represents a straightforward combination of known techniques in motion tracking, machine learning, and athletic performance analysis, thereby rendering subsequent claims of novelty invalid under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,857,862
TitleMethod and system for assessing tennis stroke heaviness